Mar 13
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Build a CrewAI loan-validation crew, wrap it behind a single A2A endpoint, and compare what role-based crews do differently from LangGraph and Microsoft Agent Framework. In this lesson, we cover CrewAI roles, goals, sequential execution, the A2A wrapper pattern, and why A2A matters when different teams choose different agent frameworks. This is part of a 16-video series designed to help you build interoperable agents with the A2A protocol. Instructor: Nilay Parikh Channel: LocalM Tuts Full Course: https://tuts.localm.dev/a2a Full Course on Youtube: https://www.youtube.com/playlist?list=PLJ0cHGb-LuN9JvtKbRw5agdZl_xKwEvz5 Timestamps: 00:00 - Intro: CrewAI in the framework tour 00:32 - Build the loan validation crew 01:15 - Practical session setup 01:37 - A2A server wrapping with CrewAI 02:28 - Run the client and pre-screening skill 03:14 - Why A2A fits polyglot agent systems 03:47 - Learning A2A through repetition and the interactive page 05:05 - CrewAI output vs LangGraph 05:55 - Choosing frameworks by use case 07:06 - CrewAI and Microsoft Agent Framework tradeoffs 09:01 - Final verdict review and wrap-up ⸻ Resources & Links ⸻ 🔗 Course Page: https://tuts.localm.dev/a2a 💻 Lesson Code: https://github.com/nilayparikh/tuts-agentic-ai-examples/tree/main/a2a/lessons/11-crewai 📄 CrewAI: https://github.com/crewAIInc/crewAI ◀️ Previous: A2A with LangGraph & MCP ▶️ Next: A2A with OpenAI Agents SDK ⸻ About this Course ⸻ This course explains how A2A gives you a protocol layer for agent interoperability while still letting each team choose the framework that fits its use case. Across the series, you compare concrete implementations so framework tradeoffs stay grounded in working examples instead of abstractions. #A2A #Agent2Agent #CrewAI #MultiAgent #LocalMTuts